面向真实物体色还原的显示色域构建与评价标准

面向真实物体色还原的显示色域构建与评价标准

随着显示技术从DCI-P3迈向BT.2020，最近的四色显示已实现超110%的BT.2020覆盖。然而，更广的色域不等于更真实的色彩。真实表面物体色的还原能力，正成为电视色彩表现的核心组成部分，它直接决定了视频内容在视觉上的自然感知程度。

现有参考色域如Pointer's Gamut样本陈旧，ISO RCG则包含非表面色，无法准确衡量真实物体的色彩还原能力。本研究基于超9.7万条光谱数据，构建了涵盖现代涂料、织物、皮肤等的真实表面色域，并联合德国莱茵TUV引入基于CAM16的感知立体色域评价体系。该体系不仅评估色域覆盖率，更关注不同亮度下的色彩还原精准度，旨在为RGB四色显示提供科学映射基准，推动行业从参数竞赛回归视觉真实。

Construction and Evaluation Standard of Display Gamut for Real Object Color Reproduction

As display technology advances from DCI-P3 toward BT.2020, recent four-primary-color displays have achieved over 110% BT.2020 coverage. However, a wider color gamut does not equate to more realistic colors. The ability to reproduce real surface object colors is becoming a core component of television color performance, as it directly determines the visual naturalness of video content.

Existing reference gamuts, such as Pointer's Gamut, are based on outdated samples, while the ISO RCG includes non-surface colors, making them inaccurate for evaluating real object color reproduction. This study constructs a real surface color gamut covering modern paints, textiles, skin, and more, based on over 97,000 spectral data points. In collaboration with TÜV Rheinland, we introduce a perceptual stereo color gamut evaluation system based on CAM16. This system not only assesses gamut coverage but also focuses on color reproduction accuracy across different luminance levels. It aims to provide a scientific mapping benchmark for RGB four-primary-color displays, steering the industry from a parameter-driven competition back to visual reality.